
import os, types
import pandas as pd
from botocore.client import Config
import ibm_boto3

def __iter__(self): return 0

# @hidden_cell
# The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials.
# You might want to remove those credentials before you share the notebook.

cos_client = ibm_boto3.client(service_name='s3',
    ibm_api_key_id='696W9JyPmRlNKHtY3s-8sBBPSmFLennhf_3obuhn63C0',
    ibm_auth_endpoint="https://iam.cloud.ibm.com/oidc/token",
    config=Config(signature_version='oauth'),
    endpoint_url='https://s3.private.eu-de.cloud-object-storage.appdomain.cloud')

bucket = 'ctr-donotdelete-pr-kp5ryzb5c6gmwg'
object_key = 'Click.csv'

body = cos_client.get_object(Bucket=bucket,Key=object_key)['Body']
# add missing __iter__ method, so pandas accepts body as file-like object
if not hasattr(body, "__iter__"): body.__iter__ = types.MethodType( __iter__, body )

df_1 = pd.read_csv(body)
df_1.head(10)


df_1.tail()


df_1.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10000 entries, 0 to 9999
Data columns (total 10 columns):
 #   Column                    Non-Null Count  Dtype  
---  ------                    --------------  -----  
 0   Daily Time Spent on Site  10000 non-null  float64
 1   Age                       10000 non-null  float64
 2   Area Income               10000 non-null  float64
 3   Daily Internet Usage      10000 non-null  float64
 4   Ad Topic Line             10000 non-null  object 
 5   City                      10000 non-null  object 
 6   Gender                    10000 non-null  object 
 7   Country                   10000 non-null  object 
 8   Timestamp                 10000 non-null  object 
 9   Clicked on Ad             10000 non-null  int64  
dtypes: float64(4), int64(1), object(5)
memory usage: 781.4+ KB


df_1.describe()


import plotly.graph_objects as go
import plotly.express as px
import plotly.io as pio
pio.templates.default

'plotly'


df_1['Clicked on Ad']=df_1["Clicked on Ad"].map({0:"No",1:"Yes"})


fig=px.box(df_1,
          x="Daily Time Spent on Site",
          color="Clicked on Ad",
          title="Click through rate based time spent on site",
          color_discrete_map={'Yes':'Pink',
                             'No':'Blue'})
fig.update_traces(quartilemethod="exclusive")
fig.show()


fig=px.box(df_1,
          x="Daily Internet Usage",
          color="Clicked on Ad",
          title="Click through rate based on Daily Internet Usage",
          color_discrete_map={'Yes':'Pink',
                             'No':'Blue'})
fig.update_traces(quartilemethod="exclusive")
fig.show()


fig=px.box(df_1,
          x="Age",
          color="Clicked on Ad",
          title="Click through rate based on Age",
          color_discrete_map={'Yes':'Pink',
                             'No':'Blue'})
fig.update_traces(quartilemethod="exclusive")
fig.show()


fig=px.box(df_1,
          x="Area Income",
          color="Clicked on Ad",
          title="Click Through Rate based on Income",
          color_discrete_map={'Yes':'Pink',
                             'No':'Blue'})
fig.update_traces(quartilemethod="exclusive")
fig.show()


df_1['Clicked on Ad'].value_counts()

No     5083
Yes    4917
Name: Clicked on Ad, dtype: int64


click_through_rate=4917/10000*100
print(click_through_rate)

49.17

	Daily Time Spent on Site	Age	Area Income	Daily Internet Usage	Ad Topic Line	City	Gender	Country	Timestamp	Clicked on Ad
0	62.26	32.0	69481.85	172.83	Decentralized real-time circuit	Lisafort	Male	Svalbard & Jan Mayen Islands	2016-06-09 21:43:05	0
1	41.73	31.0	61840.26	207.17	Optional full-range projection	West Angelabury	Male	Singapore	2016-01-16 17:56:05	0
2	44.40	30.0	57877.15	172.83	Total 5thgeneration standardization	Reyesfurt	Female	Guadeloupe	2016-06-29 10:50:45	0
3	59.88	28.0	56180.93	207.17	Balanced empowering success	New Michael	Female	Zambia	2016-06-21 14:32:32	0
4	49.21	30.0	54324.73	201.58	Total 5thgeneration standardization	West Richard	Female	Qatar	2016-07-21 10:54:35	1
5	51.30	26.0	51463.17	131.68	Focused multi-state workforce	Port Maria	Female	Cameroon	2016-05-15 13:18:34	0
6	66.08	43.0	73538.09	136.40	Optimized upward-trending productivity	Port Jeffrey	Male	Turkey	2016-04-03 21:13:46	1
7	36.08	26.0	74903.41	228.78	Programmable uniform website	East Kevinbury	Male	French Guiana	2016-03-11 06:49:10	0
8	46.14	33.0	43974.49	196.77	Customizable tangible hierarchy	Lake Annashire	Male	Vanuatu	2016-03-24 06:36:52	0
9	51.65	51.0	74535.94	188.56	Function-based incremental standardization	Edwardmouth	Female	Cameroon	2016-01-31 05:12:44	0

	Daily Time Spent on Site	Age	Area Income	Daily Internet Usage	Ad Topic Line	City	Gender	Country	Timestamp	Clicked on Ad
9995	41.73	31.0	61840.26	207.17	Profound executive flexibility	West Angelabury	Male	Singapore	2016-01-03 03:22:15	1
9996	41.73	28.0	51501.38	120.49	Managed zero tolerance concept	Kennedyfurt	Male	Luxembourg	2016-05-28 12:20:15	0
9997	55.60	39.0	38067.08	124.44	Intuitive exuding service-desk	North Randy	Female	Egypt	2016-01-05 11:53:17	0
9998	46.61	50.0	43974.49	123.13	Realigned content-based leverage	North Samantha	Female	Malawi	2016-04-04 07:07:46	1
9999	46.61	43.0	60575.99	198.45	Optimized upward-trending productivity	Port Jeffrey	Male	Northern Mariana Islands	2016-04-03 21:13:46	1

	Daily Time Spent on Site	Age	Area Income	Daily Internet Usage	Clicked on Ad
count	10000.000000	10000.000000	10000.000000	10000.000000	10000.000000
mean	61.660757	35.940100	53840.047721	177.759831	0.491700
std	15.704142	8.572973	13343.708718	40.820951	0.499956
min	32.600000	19.000000	13996.500000	105.220000	0.000000
25%	48.860000	29.000000	44052.302500	140.150000	0.000000
50%	59.590000	35.000000	56180.930000	178.920000	0.000000
75%	76.580000	42.000000	61840.260000	212.670000	1.000000
max	90.970000	60.000000	79332.330000	269.960000	1.000000